Four Research Designs and a Comprehensive Analysis Strategy for Investigating Common Method Variance with Self-Report Measures Using Latent Variables

Larry J. Williams, Alyssa K. McGonagle

Research output: Contribution to journalArticle

60 Scopus citations

Abstract

Common method variance (CMV) is an ongoing topic of debate and concern in the organizational literature. We present four latent variable confirmatory factor analysis model designs for assessing and controlling for CMV—those for unmeasured latent method constructs, Marker Variables, Measured Cause Variables, as well as a new hybrid design wherein these three types of method latent variables are used concurrently. We then describe a comprehensive analysis strategy that can be used with these four designs and provide a demonstration using the new design, the Hybrid Method Variables Model. In our discussion, we comment on different issues related to implementing these designs and analyses, provide supporting practical guidance, and, finally, advocate for the use of the Hybrid Method Variables Model. Through these means, we hope to promote a more comprehensive and consistent approach to the assessment of CMV in the organizational literature and more extensive use of hybrid models that include multiple types of latent method variables to assess CMV.

Original languageEnglish
Pages (from-to)339-359
Number of pages21
JournalJournal of Business and Psychology
Volume31
Issue number3
DOIs
StatePublished - Sep 1 2016

Keywords

  • Common method variance
  • Hybrid Method Variables Model
  • Marker Variable
  • Measured Cause Variable
  • Measured method variable
  • Unmeasured latent method factor

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